.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/annoy/plot_precision_script.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_annoy_plot_precision_script.py>`
        to download the full example code or to run this example in your browser via JupyterLite or Binder.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_annoy_plot_precision_script.py:


Precision annoy.AnnoyIndex with examples
==========================================

An example showing the :py:class:`~scikitplot.annoy.AnnoyIndex` class.

.. GENERATED FROM PYTHON SOURCE LINES 12-28

.. code-block:: Python

    from __future__ import print_function

    import random; random.seed(0)
    import time

    # from annoy import AnnoyIndex
    # from scikitplot.annoy import AnnoyIndex
    from scikitplot.annoy import Index as AnnoyIndex

    try:
        from tqdm.auto import tqdm, trange
    except ImportError:
        # Fallback: dummy versions that ignore all args/kwargs
        tqdm = lambda iterable, *args, **kwargs: iterable
        trange = lambda n, *args, **kwargs: range(n)








.. GENERATED FROM PYTHON SOURCE LINES 29-30

n, f = 1_000_000, 100  # 100~2.5GB

.. GENERATED FROM PYTHON SOURCE LINES 30-50

.. code-block:: Python

    n, f = 100_000, 100  # 100~0.25GB 256~0.6GB


    idx = AnnoyIndex(
        f=f,
        metric='angular',
    )
    idx.set_seed(0)
    for i in trange(n):
        if(i % (n//10) == 0): print(f"{i} / {n} = {1.0 * i / n}")
        # v = []
        # for z in range(f):
        #     v.append(random.gauss(0, 1))
        v = [random.gauss(0, 1) for _ in range(f)]
        idx.add_item(i, v)

    idx.build(2 * f)
    idx.save('test.annoy')
    idx.info()





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    /home/circleci/repo/galleries/examples/annoy/plot_precision_script.py:37: UserWarning:

    seed=0 resets to Annoy's default seed


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    {'f': 100, 'metric': 'angular', 'n_neighbors': 5, 'on_disk_path': 'test.annoy', 'prefault': False, 'seed': None, 'verbose': None, 'schema_version': 0, 'n_items': 100000, 'n_trees': 200, 'memory_usage_byte': 270573580, 'memory_usage_mib': 258.0390739440918}



.. GENERATED FROM PYTHON SOURCE LINES 51-83

.. code-block:: Python


    def plot(idx, y=None, **kwargs):
        import numpy as np
        import matplotlib.pyplot as plt
        import scikitplot.cexternals._annoy._plotting as utils

        single = np.zeros(idx.get_n_items(), dtype=int)
        if y is None:
            double = np.random.uniform(0, 1, idx.get_n_items()).round()

        # single vs double
        fig, ax = plt.subplots(ncols=2, figsize=(12, 5))
        alpha = kwargs.pop("alpha", 0.8)
        y2 = utils.plot_annoy_index(
            idx,
            dims = list(range(idx.f)),
            plot_kwargs={"draw_legend": False},
            ax=ax[0],
        )[0]
        utils.plot_annoy_knn_edges(
            idx,
            y2,
            k=1,
            line_kwargs={"alpha": alpha},
            ax=ax[1],
        )

    # idx.unbuild()
    # idx.build(10)
    plot(idx)





.. image-sg:: /auto_examples/annoy/images/sphx_glr_plot_precision_script_001.png
   :alt: plot precision script
   :srcset: /auto_examples/annoy/images/sphx_glr_plot_precision_script_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 84-109

.. code-block:: Python

    def precision(q):
      limits = [10, 100, 1_000, 10_000]
      k = 10
      prec_n = 10
      prec_sum = {}
      time_sum = {}

      for i in trange(prec_n):
          j = random.randrange(0, n)
          closest = set(q.get_nns_by_item(j, k, n))
          for limit in limits:
              t0 = time.time()
              toplist = q.get_nns_by_item(j, k, limit)
              T = time.time() - t0

              found = len(closest.intersection(toplist))
              hitrate = 1.0 * found / k
              prec_sum[limit] = prec_sum.get(limit, 0.0) + hitrate
              time_sum[limit] = time_sum.get(limit, 0.0) + T

      for limit in limits:
          print('limit: %-9d precision: %6.2f%% avg time: %.6fs'
          % (limit, 100.0 * prec_sum[limit] / (i + 1), time_sum[limit] / (i + 1)))









.. GENERATED FROM PYTHON SOURCE LINES 110-116

.. code-block:: Python

    q = AnnoyIndex(f, 'angular')
    q.set_seed(0)
    q.load('test.annoy')
    precision(q)






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    /home/circleci/repo/galleries/examples/annoy/plot_precision_script.py:111: UserWarning:

    seed=0 resets to Annoy's default seed


      0%|          | 0/10 [00:00<?, ?it/s]
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    100%|██████████| 10/10 [00:00<00:00, 68.22it/s]
    limit: 10        precision:  13.00% avg time: 0.000159s
    limit: 100       precision:  16.00% avg time: 0.000101s
    limit: 1000      precision:  25.00% avg time: 0.000302s
    limit: 10000     precision:  82.00% avg time: 0.001917s




.. GENERATED FROM PYTHON SOURCE LINES 117-124

.. tags::

   model-type: classification
   model-workflow: impute
   plot-type: bar
   level: beginner
   purpose: showcase


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (2 minutes 55.349 seconds)


.. _sphx_glr_download_auto_examples_annoy_plot_precision_script.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/scikit-plots/scikit-plots/maintenance/0.4.X?urlpath=lab/tree/notebooks/auto_examples/annoy/plot_precision_script.ipynb
        :alt: Launch binder
        :width: 150 px

    .. container:: lite-badge

      .. image:: images/jupyterlite_badge_logo.svg
        :target: ../../lite/lab/index.html?path=auto_examples/annoy/plot_precision_script.ipynb
        :alt: Launch JupyterLite
        :width: 150 px

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_precision_script.ipynb <plot_precision_script.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_precision_script.py <plot_precision_script.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_precision_script.zip <plot_precision_script.zip>`


.. include:: plot_precision_script.recommendations


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_